Senior Fraud Risk Modeler(Credit Card)

Job Role : Senior Fraud Risk Modeler(Credit Card)

Experience: 5+ Years

Location: Gurgaon/Bangalore

As a Senior Risk Modeler specializing in Fraud Risk, you will design, develop, and maintain models to detect and prevent fraud across various financial products and channels - primarily in the credit card domain. You’ll analyze emerging fraud trends, assess fraud risk, and support fraud prevention strategies, while clearly communicating insights to stakeholders and collaborating with cross-functional teams to enhance fraud detection capabilities and reduce fraud losses.

• Model Development & Validation

  : Build, implement, and validate fraud detection and prevention models using advanced statistical and machine learning techniques for credit card products.

• Data Analysis & Interpretation

  : Analyze large-scale transactional and behavioral data to identify fraud patterns, assess model performance, and provide actionable insights.

• Risk Assessment & Monitoring

  : Evaluate existing fraud controls, monitor fraud trends, and quantify exposure to evolving threats across digital and traditional channels.

• Communication & Collaboration

  : Effectively present analytical findings and model performance to both technical and non-technical stakeholders, including fraud operations, compliance, and executive leadership.

• Documentation & Reporting

  : Maintain comprehensive documentation of model development processes, risk assumptions, fraud detection frameworks, and compliance requirements.

• Technical Skills

  : Strong proficiency in Python, SQL, and data science tools; familiarity with real-time decision engines and fraud detection platforms is a plus. (e.g., Actimize, Falcon, SAS).

• Domain Expertise

  : Deep understanding of fraud domain expertise for debit card product.

• Leadership & Teamwork

  : Ability to lead fraud analytics initiatives, mentor junior analysts or data scientists, and collaborate with risk, IT, and fraud operations teams.

• Problem Solving

  : Proactively identify vulnerabilities in fraud strategies, recommend enhancements, and respond to emerging threats in a fast-paced environment.

• Adaptability

  : Stay current with the latest fraud schemes, detection technologies, and regulatory developments impacting fraud risk management.

Qualifications:

• Bachelors or Master’s.

  in a quantitative discipline such as Statistics, Mathematics, Computer Science, Economics, Data Science, or a related field.

• 6 to 7 years of hands-on experience in a banking environment

  , specifically in developing, implementing, and maintaining

  fraud risk models

  across products and channels.
• Proven experience in

  fraud analytics and modelling

  , including transaction monitoring, real-time detection, and rules-based or machine learning-driven approaches.
• Strong

  programming skills

  in Python, SQL, R, or SAS for model development, data manipulation, and automation.
• Proficiency with

  machine learning

  and statistical techniques such as decision trees, gradient boosting, clustering, anomaly detection, and neural networks.
• Good understanding of how

  linear regression

  and

  XGBoost

  work, including their assumptions, strengths, and limitations.
• Solid understanding of

  fraud typologies

  and fraud prevention technologies.
• Demonstrated ability to work with

  large and complex datasets

  , conduct deep-dive analytics, and extract actionable insights.
• Excellent

  communication and stakeholder management skills

  , with the ability to clearly articulate model logic, assumptions, and outcomes to non-technical audiences.
• Experience performing fraud model validation, performance monitoring, and tuning processes to ensure effectiveness and compliance.
• Strong

  problem-solving skills

  to address emerging fraud risks, data quality challenges, and operational issues.